/Invacost_SDM

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Quantifying the Hidden Costs of Biological Invasions

Abstract

Biological invasions threaten global biodiversity, human well-being and economies. Many regional and taxonomic syntheses of monetary costs have been produced recently, but all have important knowledge gaps owing to uneven geographic and taxonomic research intensity and thus data availability. To bridge these gaps, we combine species distribution models, macroeconomic data, and the most detailed global invasive species cost database available to produce the finest spatio-temporal cost estimates ( resolution ~85 km2). From a subset of 162 invasive species with “highly reliable” documented costs, our interpolation demonstrates a substantial escalation in global costs of 475% higher than previously recorded. This discrepancy was uneven geographically and taxonomically, peaking in Africa and for plants. Our results showed that damage costs were primarily driven by human population size, agricultural area and suitability area, whereas management costs correlated with Gross Domestic Product and suitability area. We also found a lag time in damage costs of 48 years, but not management expenditures. This study not only quantifies a more complete view of the economic dimensions of biological invasions, but it also pioneers methodological predictive methods and narrows the global disparity in invasion cost reporting.

Authors and Affiliations

  • Ismael Soto - University of South Bohemia in České Budějovice, Faculty of Fisheries and Protection of Waters, South Bohemian Research Center of Aquaculture and Biodiversity of Hydrocenoses, Zátiší 728/II, 389 25 Vodňany, Czech Republic. ORCID: 0000-0002-7288-6336
  • Pierre Courtois - CEE-M, University of Montpellier, CNRS, INRAE, Instit Agro, F34000, France. ORCID: 0000-0002-3997-828X
  • Arman Pili - School of Biological Sciences, Faculty of Science, Monash University, Clayton, 3800 Victoria, Australia; Institute for Biochemistry and Biology, University of Potsdam, 14469 Potsdam, Germany. ORCID:0000-0002-3952-9732
  • Enrico Tordoni - Department of Botany, Institute of Ecology and Earth Science, University of Tartu, J. Liivi 2, Tartu 50409, Estonia. ORCID: 0000-0002-9722-6692
  • Elena Manfrini - Université Paris-Saclay, CNRS, AgroParisTech, Ecologie Systématique Evolution, Gif sur Yvette, France; Unité Biologie des Organismes et Ecosystèmes Aquatiques (BOREA, UMR 8067), Muséum national d'Histoire naturelle, Sorbonne Université, Université de Caen Normandie, CNRS, IRD, Université des Antilles, Paris, France. ORCID: 0000-0002-9382-6973
  • Elena Angulo - Estación Biológica de Doñana, CSIC, Avda. Americo Vespucio 26, 41092, Seville, Spain. ORCID: 0000-0001-5545-4032
  • Céline Bellard - Université Paris-Saclay, CNRS, AgroParisTech, Ecologie Systématique Evolution, Gif sur Yvette, France. ORCID:0000-0003-2012-1160
  • Elizabeta Briski - GEOMAR Helmholtz-Zentrum für Ozeanforschung Kiel, Wischhofstraße 1-3, 24148, Kiel, Germany. ORCID: 0000-0003-1896-3860
  • Ross N. Cuthbert - Institute for Global Food Security, School of Biological Sciences, Queen’s University Belfast, Belfast, BT9 5DL, United Kingdom. ORCID: 0000-0003-2770-2544
  • Melina Kourantidou - University of Western Brittany, AMURE, Plouzané, France; Department of Sociology, Environmental and Business Economics, University of Southern Denmark, Esbjerg, Denmark; Woods Hole Oceanographic Institution, Marine Policy Center, Woods Hole, Massachusetts, United States of America. ORCID: 0000-0001-9595-3354
  • Rafael L. Macêdo - Graduate Program in Conservation and Ecotourism, Federal University of Rio de Janeiro State, Rio de Janeiro, RJ, Brazil; Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB), Müggelseedamm 310, 12587 Berlin, Germany; Institute of Biology, Freie Universität Berlin, Königin-Luise-Str. 1-3, 14195 Berlin, Germany. ORCID: 0000-0001-5086-0170
  • Boris Leroy - Unité Biologie des Organismes et Ecosystèmes Aquatiques (BOREA, UMR 8067), Muséum national d'Histoire naturelle, Sorbonne Université, Université de Caen Normandie, CNRS, IRD, Université des Antilles, Paris, France. ORCID: 0000-0002-7686-4302
  • Phillip J. Haubrock - University of South Bohemia in České Budějovice, Faculty of Fisheries and Protection of Waters, South Bohemian Research Center of Aquaculture and Biodiversity of Hydrocenoses, Zátiší 728/II, 389 25 Vodňany, Czech Republic; Department of River Ecology and Conservation, Senckenberg Research Institute and Natural History Museum Frankfurt, Gelnhausen, Germany; CAMB, Center for Applied Mathematics and Bioinformatics, Gulf University for Science and Technology, Kuwait. ORCID: 0000-0003-2154-4341
  • Franck Courchamp - Université Paris-Saclay, CNRS, AgroParisTech, Ecologie Systématique Evolution, Gif sur Yvette, France. ORCID: 0000-0001-7605-4548
  • Brian Leung - Department of Biology, McGill University, Montréal, QC, Canada; Bieler School of Environment, McGill University, Montreal, QC, Canada. ORCID: 0000-0002-8323-9628

✝Corresponding authors: Ismael Soto & Brian Leung

Prerequisites

  • R (version 4.0.0 or higher) --> I used v4.3.1
  • Required R packages: dismo, rgdal, raster, rgbif, stringr, raster, sf,rgeos,invacost, tidyr,caret,pROC, tmap,mgcv,gridExtra

Codes

  • Interpolation_costs

Data